Overview

Dataset statistics

Number of variables11
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.1 KiB
Average record size in memory88.1 B

Variable types

NUM10
BOOL1

Warnings

X0 has unique values Unique
X1 has unique values Unique
X2 has unique values Unique
X3 has unique values Unique
X4 has unique values Unique
X5 has unique values Unique
X6 has unique values Unique
X7 has unique values Unique
X8 has unique values Unique
X9 has unique values Unique

Reproduction

Analysis started2020-12-15 20:04:57.174195
Analysis finished2020-12-15 20:05:20.846775
Duration23.67 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

X0
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.03307974084
Minimum-3.839985809
Maximum3.201792641
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:20.948323image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.839985809
5-th percentile-1.707186948
Q1-0.7120824422
median-0.01510937921
Q30.5912908356
95-th percentile1.658395949
Maximum3.201792641
Range7.04177845
Interquartile range (IQR)1.303373278

Descriptive statistics

Standard deviation1.021897108
Coefficient of variation (CV)-30.8919321
Kurtosis0.1712298219
Mean-0.03307974084
Median Absolute Deviation (MAD)0.6480965717
Skewness-0.06835959853
Sum-33.07974084
Variance1.044273699
MonotocityNot monotonic
2020-12-15T21:05:21.170413image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.16538565110.1%
 
0.360721225110.1%
 
1.75252243210.1%
 
-0.855913529910.1%
 
-0.942905822410.1%
 
0.379125029110.1%
 
0.0719680671610.1%
 
-0.633349963610.1%
 
-0.506840525710.1%
 
0.212254608710.1%
 
0.493634475210.1%
 
0.77973810710.1%
 
0.928598887510.1%
 
-0.85245559910.1%
 
-0.769813528210.1%
 
-0.181177756310.1%
 
0.573748269410.1%
 
0.114444301510.1%
 
-0.175000407910.1%
 
0.552408949410.1%
 
0.593901592410.1%
 
2.19238749410.1%
 
0.867735250410.1%
 
0.00097068826610.1%
 
-0.881202992210.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.83998580910.1%
 
-3.50391498410.1%
 
-2.88256261410.1%
 
-2.85093438210.1%
 
-2.84787407310.1%
 
-2.79777973610.1%
 
-2.61505145210.1%
 
-2.60930724710.1%
 
-2.53072046510.1%
 
-2.50846118610.1%
 
ValueCountFrequency (%) 
3.20179264110.1%
 
3.18492971710.1%
 
2.8149180110.1%
 
2.59370968710.1%
 
2.51786469910.1%
 
2.47835107710.1%
 
2.41118490810.1%
 
2.36242410210.1%
 
2.35311342210.1%
 
2.28017115510.1%
 

X1
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003910785122
Minimum-3.012088554
Maximum3.032491837
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:21.407176image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.012088554
5-th percentile-1.59925116
Q1-0.6678383336
median-0.007053760341
Q30.6914193622
95-th percentile1.690815674
Maximum3.032491837
Range6.044580391
Interquartile range (IQR)1.359257696

Descriptive statistics

Standard deviation1.009275895
Coefficient of variation (CV)258.0750063
Kurtosis-0.009928368221
Mean0.003910785122
Median Absolute Deviation (MAD)0.6807089878
Skewness0.05301036227
Sum3.910785122
Variance1.018637832
MonotocityNot monotonic
2020-12-15T21:05:21.613663image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.788786061410.1%
 
0.170313412610.1%
 
-1.10101305910.1%
 
-1.03161525510.1%
 
-0.127019231510.1%
 
-0.153665218910.1%
 
-0.911723254810.1%
 
0.269983098910.1%
 
-0.163374941510.1%
 
0.0477032181210.1%
 
0.794520090710.1%
 
0.524907327810.1%
 
-1.5084791210.1%
 
0.866719830110.1%
 
0.0140661608910.1%
 
1.61539811610.1%
 
-1.11606985410.1%
 
0.278580164610.1%
 
-0.345619789410.1%
 
-1.55908799510.1%
 
0.366120215310.1%
 
0.900997838610.1%
 
0.34423142510.1%
 
-0.303441750510.1%
 
1.05633817310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.01208855410.1%
 
-2.68589073210.1%
 
-2.6585354310.1%
 
-2.64857982210.1%
 
-2.62315782210.1%
 
-2.59841358310.1%
 
-2.55591803710.1%
 
-2.54320914710.1%
 
-2.53528303710.1%
 
-2.51370356510.1%
 
ValueCountFrequency (%) 
3.03249183710.1%
 
3.00467911510.1%
 
2.91533229210.1%
 
2.81783185110.1%
 
2.78471814310.1%
 
2.67836933910.1%
 
2.58420860710.1%
 
2.54730203310.1%
 
2.48264537110.1%
 
2.41617802110.1%
 

X2
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04033313698
Minimum-3.534321298
Maximum3.688817836
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:21.854031image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.534321298
5-th percentile-1.619695933
Q1-0.6095983974
median0.02511581097
Q30.7374471485
95-th percentile1.6444159
Maximum3.688817836
Range7.223139134
Interquartile range (IQR)1.347045546

Descriptive statistics

Standard deviation0.9931912128
Coefficient of variation (CV)24.62469541
Kurtosis0.04668772674
Mean0.04033313698
Median Absolute Deviation (MAD)0.6739611839
Skewness-0.0535143756
Sum40.33313698
Variance0.9864287852
MonotocityNot monotonic
2020-12-15T21:05:22.077562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.454412281210.1%
 
-0.300790182710.1%
 
0.585759010610.1%
 
-1.86860382410.1%
 
0.45327557910.1%
 
-1.45051083110.1%
 
0.305342856710.1%
 
1.49753426810.1%
 
-0.29555942110.1%
 
-0.666022999310.1%
 
-0.142875106210.1%
 
-1.43916257310.1%
 
0.556369559410.1%
 
0.553301701810.1%
 
0.0228355047310.1%
 
-0.67313398610.1%
 
-1.40349283810.1%
 
-0.468342715710.1%
 
-0.984767791810.1%
 
-0.829924603510.1%
 
-0.379878914610.1%
 
-0.515004116110.1%
 
-0.629235597610.1%
 
0.648714048910.1%
 
-0.865346114710.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.53432129810.1%
 
-3.3358961810.1%
 
-2.8062082410.1%
 
-2.77488845810.1%
 
-2.70241739510.1%
 
-2.39241269710.1%
 
-2.36837018210.1%
 
-2.35910497510.1%
 
-2.34536749310.1%
 
-2.31277395310.1%
 
ValueCountFrequency (%) 
3.68881783610.1%
 
2.72173560810.1%
 
2.61287210910.1%
 
2.50657858210.1%
 
2.43817862910.1%
 
2.40836262310.1%
 
2.38934957310.1%
 
2.37991937510.1%
 
2.36254086910.1%
 
2.34490102610.1%
 

X3
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09457988548
Minimum-3.539512099
Maximum3.261001838
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:22.312837image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.539512099
5-th percentile-1.470561183
Q1-0.6001637688
median0.0625476073
Q30.7671018207
95-th percentile1.763999848
Maximum3.261001838
Range6.800513937
Interquartile range (IQR)1.36726559

Descriptive statistics

Standard deviation1.004737182
Coefficient of variation (CV)10.62315922
Kurtosis-0.0302015733
Mean0.09457988548
Median Absolute Deviation (MAD)0.6902341788
Skewness0.04884531418
Sum94.57988548
Variance1.009496805
MonotocityNot monotonic
2020-12-15T21:05:22.525033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-1.6447353910.1%
 
0.65602547210.1%
 
0.398895691410.1%
 
-1.34215179610.1%
 
-0.645117642610.1%
 
-0.0396974032110.1%
 
0.080932932310.1%
 
0.94728871810.1%
 
-0.3317024410.1%
 
-2.31855939410.1%
 
-0.944352830510.1%
 
1.82415564610.1%
 
-1.51421463310.1%
 
1.19319100910.1%
 
0.227416912710.1%
 
0.304663244510.1%
 
-1.05571407310.1%
 
0.541432236610.1%
 
0.943489019110.1%
 
0.603266047810.1%
 
0.182706235810.1%
 
-0.0502117253410.1%
 
0.531114262810.1%
 
-0.896638136610.1%
 
-0.039184819410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.53951209910.1%
 
-2.81930608110.1%
 
-2.80745943510.1%
 
-2.74942926810.1%
 
-2.58382904510.1%
 
-2.55075774610.1%
 
-2.50283435610.1%
 
-2.37780946310.1%
 
-2.3471588310.1%
 
-2.31855939410.1%
 
ValueCountFrequency (%) 
3.26100183810.1%
 
2.96320678110.1%
 
2.87597456510.1%
 
2.85520385110.1%
 
2.7833646910.1%
 
2.65022887510.1%
 
2.5973751210.1%
 
2.58441927510.1%
 
2.50859035710.1%
 
2.47529420210.1%
 

X4
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.01640179091
Minimum-3.300360909
Maximum3.201318936
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:22.750372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.300360909
5-th percentile-1.667322303
Q1-0.668657903
median-0.02186816787
Q30.6335325656
95-th percentile1.599178756
Maximum3.201318936
Range6.501679845
Interquartile range (IQR)1.302190469

Descriptive statistics

Standard deviation0.989091519
Coefficient of variation (CV)-60.30387319
Kurtosis-0.006565746804
Mean-0.01640179091
Median Absolute Deviation (MAD)0.6546579346
Skewness-0.02078554096
Sum-16.40179091
Variance0.978302033
MonotocityNot monotonic
2020-12-15T21:05:22.950536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-1.21905918610.1%
 
-0.517588146610.1%
 
0.750604134910.1%
 
0.574579243110.1%
 
-1.88053737610.1%
 
-0.445370625110.1%
 
-0.370009937710.1%
 
-0.162278348510.1%
 
1.59895442910.1%
 
-1.89983125210.1%
 
-1.71877378310.1%
 
0.269766114810.1%
 
0.0702636923710.1%
 
0.208297326610.1%
 
0.19298952110.1%
 
-0.443595678610.1%
 
-0.665245201510.1%
 
-0.146826198910.1%
 
1.29246879410.1%
 
1.85184036510.1%
 
-0.487165721310.1%
 
1.38730557110.1%
 
0.464410623810.1%
 
1.06566724610.1%
 
1.00363665310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.30036090910.1%
 
-3.15072535310.1%
 
-3.05818988810.1%
 
-2.97515488410.1%
 
-2.64251858510.1%
 
-2.61208275210.1%
 
-2.56861079910.1%
 
-2.41054823210.1%
 
-2.38254737210.1%
 
-2.20543320710.1%
 
ValueCountFrequency (%) 
3.20131893610.1%
 
2.76158829910.1%
 
2.74079711610.1%
 
2.58144675210.1%
 
2.57277752910.1%
 
2.44056187710.1%
 
2.36849690310.1%
 
2.352867510.1%
 
2.34021136110.1%
 
2.26480995610.1%
 

X5
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0005870046366
Minimum-3.652422252
Maximum3.087427858
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:23.177263image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.652422252
5-th percentile-1.597134376
Q1-0.6287147758
median0.02262491454
Q30.6512277644
95-th percentile1.495778605
Maximum3.087427858
Range6.73985011
Interquartile range (IQR)1.27994254

Descriptive statistics

Standard deviation0.959755479
Coefficient of variation (CV)1635.004937
Kurtosis0.1131051811
Mean0.0005870046366
Median Absolute Deviation (MAD)0.6459339571
Skewness-0.0980831739
Sum0.5870046366
Variance0.9211305795
MonotocityNot monotonic
2020-12-15T21:05:23.390668image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-1.43409277510.1%
 
0.056722725810.1%
 
0.517702611410.1%
 
0.568615771110.1%
 
-2.04056953510.1%
 
0.869476507810.1%
 
-2.21652675510.1%
 
0.229004453910.1%
 
0.0570243806110.1%
 
0.517715803310.1%
 
-0.0557029081810.1%
 
-0.145630431210.1%
 
-0.183392916810.1%
 
-0.680509429610.1%
 
-0.207278609610.1%
 
-0.295912891810.1%
 
0.477070407110.1%
 
-0.0377116318810.1%
 
-0.748844549610.1%
 
-0.116408956810.1%
 
0.253459631310.1%
 
-0.0520357255410.1%
 
1.6298623510.1%
 
1.20436349510.1%
 
1.0778726410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.65242225210.1%
 
-2.87963680910.1%
 
-2.7339968910.1%
 
-2.65693639110.1%
 
-2.58543369210.1%
 
-2.49013170810.1%
 
-2.30133478910.1%
 
-2.27767370110.1%
 
-2.25109684410.1%
 
-2.24967554710.1%
 
ValueCountFrequency (%) 
3.08742785810.1%
 
2.86564477110.1%
 
2.84073118710.1%
 
2.699151710.1%
 
2.62264199510.1%
 
2.58981604610.1%
 
2.58844775510.1%
 
2.48545659610.1%
 
2.25286684910.1%
 
2.23981888210.1%
 

X6
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01463412316
Minimum-3.36976796
Maximum2.937761319
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:23.622098image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.36976796
5-th percentile-1.616486099
Q1-0.6978211257
median0.02628105822
Q30.6929978874
95-th percentile1.657670941
Maximum2.937761319
Range6.307529278
Interquartile range (IQR)1.390819013

Descriptive statistics

Standard deviation1.012193201
Coefficient of variation (CV)69.166645
Kurtosis0.0681608991
Mean0.01463412316
Median Absolute Deviation (MAD)0.6933416228
Skewness-0.09048744849
Sum14.63412316
Variance1.024535077
MonotocityNot monotonic
2020-12-15T21:05:23.963415image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.340190522410.1%
 
1.70063871310.1%
 
-1.20694367510.1%
 
-1.59401376210.1%
 
1.86669121110.1%
 
0.0525029482510.1%
 
-0.154622735310.1%
 
0.153503771510.1%
 
-1.34135304410.1%
 
0.862915500410.1%
 
1.55456406310.1%
 
-0.532404770710.1%
 
0.562367820510.1%
 
-0.335280597210.1%
 
-1.14339503410.1%
 
0.374110350510.1%
 
-0.0106238893710.1%
 
-0.574604694610.1%
 
-0.69173904110.1%
 
0.0999119321310.1%
 
0.636070734210.1%
 
1.77795115910.1%
 
-0.0166654346810.1%
 
-0.0927392446110.1%
 
0.777487303310.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.3697679610.1%
 
-3.36443301810.1%
 
-3.10193450410.1%
 
-3.07785624410.1%
 
-2.78632979910.1%
 
-2.75929431910.1%
 
-2.73831913110.1%
 
-2.63569849710.1%
 
-2.59950438710.1%
 
-2.58666097210.1%
 
ValueCountFrequency (%) 
2.93776131910.1%
 
2.68946916810.1%
 
2.59720712410.1%
 
2.56151747810.1%
 
2.54112895110.1%
 
2.5168209710.1%
 
2.47556922410.1%
 
2.41784102710.1%
 
2.39075350110.1%
 
2.38223502110.1%
 

X7
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04333143036
Minimum-3.422096018
Maximum3.040344815
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:24.189089image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.422096018
5-th percentile-1.519868659
Q1-0.6937072434
median0.04531035085
Q30.7115610074
95-th percentile1.777654052
Maximum3.040344815
Range6.462440832
Interquartile range (IQR)1.405268251

Descriptive statistics

Standard deviation1.013014076
Coefficient of variation (CV)23.37827456
Kurtosis-0.1055526308
Mean0.04333143036
Median Absolute Deviation (MAD)0.7088979784
Skewness0.1389222316
Sum43.33143036
Variance1.026197519
MonotocityNot monotonic
2020-12-15T21:05:24.405107image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.09121343510.1%
 
-0.277329867410.1%
 
-0.691678603410.1%
 
-0.336212146110.1%
 
-0.359788500310.1%
 
1.94795079510.1%
 
0.34512224910.1%
 
-0.376064536310.1%
 
1.11602771210.1%
 
0.278637235310.1%
 
0.350137034910.1%
 
0.621598941510.1%
 
-0.720952287610.1%
 
0.192397152710.1%
 
-0.412392879110.1%
 
-1.7245010510.1%
 
1.82185940910.1%
 
0.105072455210.1%
 
0.636325465710.1%
 
-0.478838335110.1%
 
-0.951316176210.1%
 
1.63867286510.1%
 
-0.448972246310.1%
 
-0.0366129645810.1%
 
-1.51208281810.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.42209601810.1%
 
-2.67253607510.1%
 
-2.60807296410.1%
 
-2.59541562310.1%
 
-2.5553824310.1%
 
-2.39317955510.1%
 
-2.38510544510.1%
 
-2.28564434110.1%
 
-2.17753218110.1%
 
-2.16789827710.1%
 
ValueCountFrequency (%) 
3.04034481510.1%
 
3.0320903810.1%
 
2.96684687710.1%
 
2.76600286210.1%
 
2.74220955910.1%
 
2.67475342810.1%
 
2.63729744110.1%
 
2.62030654610.1%
 
2.61266881510.1%
 
2.5629694310.1%
 

X8
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02921933573
Minimum-2.916253166
Maximum3.007412381
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:24.618203image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2.916253166
5-th percentile-1.638718981
Q1-0.6614854097
median0.01338420388
Q30.7204040427
95-th percentile1.714613557
Maximum3.007412381
Range5.923665547
Interquartile range (IQR)1.381889452

Descriptive statistics

Standard deviation1.022499895
Coefficient of variation (CV)34.99394731
Kurtosis-0.2131710765
Mean0.02921933573
Median Absolute Deviation (MAD)0.6920100567
Skewness0.01064283174
Sum29.21933573
Variance1.045506035
MonotocityNot monotonic
2020-12-15T21:05:24.837189image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.615147654410.1%
 
-0.325900280910.1%
 
-0.0787492109410.1%
 
-1.52849452810.1%
 
1.01509997210.1%
 
0.0312666449410.1%
 
-0.355321383810.1%
 
0.620548997410.1%
 
-0.224647047910.1%
 
-0.471634891810.1%
 
-1.99826047810.1%
 
0.821202912910.1%
 
0.221111064110.1%
 
-1.49535840810.1%
 
-1.00130163510.1%
 
-1.47502296110.1%
 
-0.311111225510.1%
 
-1.40191577210.1%
 
0.404797164810.1%
 
1.75574771210.1%
 
-0.320222110610.1%
 
-0.228921201510.1%
 
-0.527170284810.1%
 
0.314625732110.1%
 
-1.64089893410.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-2.91625316610.1%
 
-2.79889325110.1%
 
-2.57525266810.1%
 
-2.48594168910.1%
 
-2.47722801310.1%
 
-2.46731472210.1%
 
-2.45423776110.1%
 
-2.44067719210.1%
 
-2.43148568510.1%
 
-2.32571366410.1%
 
ValueCountFrequency (%) 
3.00741238110.1%
 
2.94491003610.1%
 
2.8212406710.1%
 
2.7654204610.1%
 
2.65638240810.1%
 
2.64151541310.1%
 
2.52417884810.1%
 
2.45477360410.1%
 
2.41032240510.1%
 
2.37003640410.1%
 

X9
Real number (ℝ)

UNIQUE

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.04619095177
Minimum-3.217092555
Maximum3.615407837
Zeros0
Zeros (%)0.0%
Memory size7.9 KiB
2020-12-15T21:05:25.065954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3.217092555
5-th percentile-1.79018731
Q1-0.7287546891
median-0.05705400322
Q30.7075094199
95-th percentile1.560863712
Maximum3.615407837
Range6.832500391
Interquartile range (IQR)1.436264109

Descriptive statistics

Standard deviation1.040155683
Coefficient of variation (CV)-22.51860251
Kurtosis-0.08706380439
Mean-0.04619095177
Median Absolute Deviation (MAD)0.7145136147
Skewness-0.04699486395
Sum-46.19095177
Variance1.081923844
MonotocityNot monotonic
2020-12-15T21:05:25.278021image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-0.439886459610.1%
 
-0.209403035710.1%
 
0.632645444710.1%
 
0.552744985210.1%
 
0.964508050110.1%
 
-0.765919157410.1%
 
-0.840258868410.1%
 
-2.18867552510.1%
 
-0.84970019310.1%
 
-0.707149509610.1%
 
-0.386050811510.1%
 
0.491948011310.1%
 
-0.510924946210.1%
 
-0.744949767510.1%
 
-0.454172025310.1%
 
0.545832823910.1%
 
-0.0101176949710.1%
 
2.23029889410.1%
 
-0.481019254910.1%
 
-0.229557739410.1%
 
2.54738843710.1%
 
-0.355160947510.1%
 
0.201099904910.1%
 
1.03991113710.1%
 
-0.922147630110.1%
 
Other values (975)97597.5%
 
ValueCountFrequency (%) 
-3.21709255510.1%
 
-2.81667847610.1%
 
-2.80226186410.1%
 
-2.76380401810.1%
 
-2.74488920910.1%
 
-2.64998122710.1%
 
-2.61292910410.1%
 
-2.60357384910.1%
 
-2.59803082510.1%
 
-2.49774881810.1%
 
ValueCountFrequency (%) 
3.61540783710.1%
 
3.1708250610.1%
 
2.78750318510.1%
 
2.71900103610.1%
 
2.56818589910.1%
 
2.55874838310.1%
 
2.54738843710.1%
 
2.51777051210.1%
 
2.27550983110.1%
 
2.23029889410.1%
 

y
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
1
500 
0
500 
ValueCountFrequency (%) 
150050.0%
 
050050.0%
 
2020-12-15T21:05:25.443121image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Interactions

2020-12-15T21:04:58.096696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:58.329331image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:58.555288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:58.787730image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:59.006712image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:59.218733image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:59.434709image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:59.659208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:04:59.876190image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:00.096196image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:00.319394image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:00.741503image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:01.937401image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:02.149596image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:02.357844image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:02.996848image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:03.425836image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:03.645300image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:05.755573image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:05.965914image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:06.175875image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:06.380873image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:06.589245image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:06.802274image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:07.005512image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:07.201916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:07.621854image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:07.962049image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:08.332784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:08.574793image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:08.790271image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:09.008898image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:09.224522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:09.434427image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:09.648813image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:09.870635image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:10.088013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:10.297603image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:10.500666image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:10.711459image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:10.915804image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:11.335172image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:11.557906image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:11.766906image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:11.983879image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:12.194886image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:12.398386image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:12.608585image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:12.809803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:13.007177image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:13.216089image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:13.420993image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:13.636550image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:13.849104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:14.060084image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:14.822706image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:15.032466image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:15.236418image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:15.447039image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:15.655022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:15.877490image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:16.092856image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:16.314128image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:16.525928image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:16.737731image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:16.968176image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:17.187537image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:17.395220image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2020-12-15T21:05:17.819335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:18.040990image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:18.261763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:18.483249image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:18.696816image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:18.907341image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:19.115214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:19.324763image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:19.543344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:19.761162image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2020-12-15T21:05:25.561678image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-15T21:05:25.849710image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-15T21:05:26.141301image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-15T21:05:26.431954image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-15T21:05:20.136421image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-15T21:05:20.669645image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

X0X1X2X3X4X5X6X7X8X9y
0-1.3610020.334796-0.077620-0.1346541.2585530.360895-2.158884-0.848922-0.376171-0.0914151
1-1.6024440.1363890.251907-0.1399860.1809430.396670-0.3224591.6386731.2713741.7452480
20.4139200.3315780.5331100.1233600.359814-1.635079-0.9800650.1327830.821203-0.7659190
3-0.221102-1.164185-1.4472891.0891331.9898982.239180-0.3934770.4673411.7770460.1330891
4-0.942906-0.3456201.913583-1.298526-0.427453-0.165193-0.396326-0.064126-1.154804-0.7284220
5-0.2812050.4974280.468349-0.704690-0.5820540.7666980.509687-1.5182051.191263-0.0137900
60.313209-0.8493601.380686-0.519457-2.0348490.223009-1.6002300.309194-0.757451-1.0990370
70.5732330.8776721.411473-0.979042-0.7214900.482627-0.6854630.833349-0.346573-0.2506650
8-1.829649-0.164775-0.3729750.070525-0.0322920.929339-0.9738321.029568-1.0706080.8272130
9-0.0627850.0662290.547042-1.1527611.614771-0.659658-0.696118-0.5519130.143040-1.4915220

Last rows

X0X1X2X3X4X5X6X7X8X9y
9900.6795230.576365-1.622849-0.0989680.768397-0.340085-0.4855530.0838880.4482030.6895200
991-0.848913-0.859441-0.0962501.7365210.9807592.8656450.417508-0.2707950.551598-1.7882751
992-0.9756390.1030200.3406890.7057600.4829170.480487-1.0689042.3740210.197429-0.9057800
993-0.226137-1.0626370.553302-0.707818-0.333336-0.0307770.813517-0.6906290.091834-0.7025891
9940.0846260.323356-0.6775850.5804020.7723980.668447-0.2115540.131978-1.092915-1.7578401
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